This paper discusses the development of an individual based simulation of interventions for better treatment of patients with abdominal aortic aneurysms (AAA). The interdisciplinary subject required collaboration of medical doctors, Health Technology Assessment (HTA) experts and modelers.

Emergency Departments (EDs) require advanced support systems for monitoring and controlling their processes: clinical, operational, and financial. A prerequisite for such a system is comprehensive operational information (e.g. queueing times, busy resources,…), reliably portraying and predicting ED status as it evolves in time. To this end, simulation comes to the rescue, through a two-step procedure that is hereby proposed for supporting real-time ED control.

By creating an integrated simulation environment that models the underlying structure of a pharmaceutical enterprise portfolio it becomes possible to identify the optimal longitudinal allocation of finite resources across the constellation of available investment opportunities. The implementation of a hybrid approach that integrates multiple modeling techniques and analytic disciplines allows for a comprehensive environment that captures the underlying dynamics that drive observed market behavior. The implementation of an object oriented model structure constrains the models complexity by supporting dynamic re-use of both structure and logic.

This paper explores the problem of fragmenting social networks enabled by spatial distancing between distinct socioeconomic classes. Such fragmentation is evidenced by the experience of urban sprawl without population growth. We develop a prototype model to examine the spatial dynamics of social network evolution in the face of neighborhood migration. This model draws upon the small world analogy by using an initial template of connections that are “rewired” over time. Spatially, connections are established for neighborhood proximity. Socially, connections are added based upon similarity of economic class.

The objective of this paper was to determine the effects of adding a healthcare provider in triage on average length of stay (LOS) and proportion of patients with >6 h LOS. The other goal was to assess the accuracy of computer simulation in predicting the magnitude of such effects on these metrics.